The Economist's most reused dataset is not behind the paywall at all. It sits in a public repository, going back to April 2000.
Plans from €169/month · Free project assessment · Reply within 1 business day
ScrapeIt runs the collection as a managed service. We collect the Big Mac index as published, keep every release versioned, join it to the other data you need, and hand back CSV, JSON, Excel or a push into your warehouse.
Article records and citations from other outlets run in the same pipeline, with the source type on every row.
We do not collect behind the paywall. We collect only publicly available data - everything a visitor can see on The Economist - and we collect it legally.
Big Mac index records carry the date, ISO country code, currency code, country name, local price, dollar exchange rate, dollar price, the raw valuation against the dollar, euro, pound, yen and yuan, the GDP-based adjustment, the adjusted price and the adjusted valuations - exactly as published.
We keep the published values rather than recomputing them. The methodology is public and could be reproduced, but a recomputed index is our number, not The Economist's, and the difference matters to anyone citing it.
Article records carry the headline, section, issue date, byline where given and article identifier, as a visitor sees them without a subscription.
Citation records, built without the site, show where other outlets cite Economist analysis.
Every row carries the collection timestamp and its source type.
Index versioning is the most useful service here: every published release kept with its date, so revisions become visible and a series can be reproduced exactly as it stood at any point.
Joining the index to macroeconomic data - exchange rates, inflation, wage series from official statistics - is the usual analytical step, and it is cleaner when the index arrives with ISO codes intact, as it is published.
Citation analysis shows where Economist analysis is picked up elsewhere, without collecting the site.
Limits: we never log in and do not attempt to get past the paywall, so subscriber-only text is not part of the dataset.
The Economist is a weekly publication on international affairs, business and economics, known for its analysis and its data journalism. Its journalism sits behind a subscription, while headlines, sections and issue dates stay visible to every visitor.
Its data team's best known work is the Big Mac index, the burger-based measure of currency valuation, published with its methodology.
The index goes back to April 2000 and carries, for each country and date, the local price, the dollar exchange rate, the dollar price, the raw index against several major currencies, and an adjusted version that accounts for GDP per person.
Those two layers define what a project here can be: the index in full, and the public layer of the articles.
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Delivery: CSV, JSON or XLSX files, our API or a JSON feed. MCP server on request.
Full plan details →Requests that name The Economist tend to want one of two things: its data, or its journalism. They have very different answers.
For data, the publication has done part of the work already. The Big Mac index is published with its methodology, which means it can be collected, versioned and joined to a client's own economic data without touching the paywall at all. The index is updated periodically, so keeping each published release rather than overwriting it is what allows anyone to see how estimates were revised.
For journalism, the answer is the public layer: headline, section, issue date and article identifier, which is enough to track what the paper covers and when. Subscriber-only text stays behind the paywall and we do not collect it.
Learn how to use web scraping to solve data problems for your organization
Leveraging advances in technology, the AI-powered web scraper has skyrocketed in demand and is helping to expand capabilities by automating tedious daily tasks and speeding up data collection from thousands of websites several times over.
Web scraping is a method of obtaining web data by extracting it from pages of web resources with the help of a program, that is, in automatic mode. It is used to syntactically convert web pages into more usable forms.
If you specialize in machine learning, you need to feed large amounts of data to the algorithms. Web scraping is the easiest and the most efficient method of collecting the data from all over the Internet.
ScrapeIt is a managed extraction company, not a tool you have to learn. Our team keeps each index release versioned, follows the source as its structure changes, and keeps published values exactly as published.
You see a sample first, in your format, over the countries and currencies you actually use, so you can check the values against the published index yourself.
Yes, the public layer of them: headline, section, issue date, byline where given and article identifier, as every visitor sees them. We never log in and never go behind the paywall, so subscriber-only text is not part of the dataset.
The Big Mac index first: it goes back to April 2000, with raw and GDP-adjusted valuations against five major currencies. Article records add headline, section, issue date and article identifier.
No. We keep the published values. The methodology is public and could be reproduced, but a recomputed index would be our number rather than The Economist's, and that difference matters to anyone citing it.
Because the index is updated periodically and estimates can be revised. Keeping each release with its date lets you reproduce the series exactly as it stood at any point, which overwriting would destroy.
Yes. The ScrapeIt Economist API returns date, ISO country code, local price, dollar price and the raw and adjusted valuations as JSON from an endpoint we host, refreshed on the schedule you set. The same data also comes as CSV or XLSX files or straight into your database.
Step 1 - Make a Request
You share your needs, expectations, and desired timeframe. We’ll suggest the best solution based on your request and budget.
Step 2 - Configuring Custom Web Crawlers
Our specialists configure the crawlers and extract a sample dataset for your review before proceeding with the full-scale extraction.
Step 3 - Collect and Deliver
Once you approve the sample, we launch the project and start full data collection. We gather, filter, and structure the data for easy use, delivering it on time in your preferred format.
Step 4 - Maintain and Support
Our team manages ongoing processes, monitors website changes, and supports all data extraction cycles. We can also help integrate data into your systems or create dashboards to simplify analysis.
The Economist data from €169/month. Free project assessment, reply within 1 business day.
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